In wireless communication standards such as IEEE 802.11az, indoor localization techniques are expected to achieve submeter accuracy for security and/or privacy applications. Motivated by this background, we propose a new receive signal strength indicator (RSSI)-based localization technique using segmented convolution neural network (CNN) regression, which can be applicable for legacy devices. Specifically, assuming a testbed partitioned into certain subregions, the proposed technique estimates a subregion as a coarse estimate by using a K-nearest neighbors (KNN) algorithm, and it refines the position estimate by performing a CNN regression whose model is trained per each subregion. The experiment results using measurement data verified that the proposed technique achieves mean absolute error (MAE) of 0.34m by reducing more than 0.2m from those of the conventional cascade-connected artificial neural network (CC-ANN) and extreme gradient boosting (XGBoost) methods. In addition, the simulation results confirmed that the proposed technique reduces costs needed to make a fingerprint database to 7% of that of the XGBoost in indoor propagation channels generated from a ray-tracing model.

Polar codes are known for their good performance relative to other channel codes in the short-code regime. Thus they are suitable for internet of things (IoT) applications that have short transmission bursts and require low latency. To improve the communication reliability and throughput without significantly increasing the transmission power, hybrid automatic repeat request (HARQ) is often used. In this paper, we propose two new algorithms to decide on the number of re-transmission bits in an incremental redundancy (IR) HARQ system with short code length. The first algorithm is based on achieving a certain sequence of probabilities of successful decoding in retransmissions. The second maximizes the expected throughput of the HARQ system. We consider additive white Gaussian noise (AWGN) and Markov model for the block fading channel. The equivalent-length-based method is applied in our system to achieve higher throughput. For both designs, we derive an upper bound on the throughput. Simulations show that the proposed methods outperform the existing methods. We also apply our designs to a non-orthogonal multiple access (NOMA) system. In the NOMA system, we approximate parameters used in our algorithms to prevent storing too many parameters of the combination of the signal-to-noise ratio (SNR). It is found that the set of information bits should be chosen carefully to avoid puncturing bits with high reliability.

Industry and academia have been working towards the evolution from Centralized massive Multiple-Input Multiple-Output (CmMIMO) to Distributed mMIMO (DmMIMO) architectures. Instead of splitting a coverage area into many cells, each served by a single Base Station equipped with several antennas, the whole coverage area is jointly covered by several Access Points (AP) equipped with few or single antennas. Nevertheless, when choosing between deploying more APs with few or single antennas or fewer APs equipped with many antennas, one observes an inherent trade-off between the beamforming and macro-diversity gains that has not been investigated in the literature. Given a total number of antenna elements and total downlink power, under a channel model that takes into account a probability of Line-of-Sight (LoS) as a function of the distance between the User Equipments (UEs) and APs, our numerical results show that there exists a “sweet spot” on the optimal number of APs and of antenna elements per AP which is a function of the physical dimensions of the coverage area.

Millimeter wave (mmWave) communication is a promising technology in the 5G and beyond communications. Because of the ultra-high frequency, the mmWave communication suffers from significant path loss and the number of paths from users to the base station (BS) is much fewer than that in the conventional wireless communications systems. These problems can be mitigated by exploiting massive multi-input multi-output (MIMO) and beamforming techniques. To obtain the channel information for MIMO systems, the pilot-based channel estimation may incur a large overhead as the numbers of users and antennas increase. In this paper, we propose a blind channel estimation method for mmWave uplink that avoids using pilot signals. With the number of users unknown, we first estimate the number of users by the rank of the correlation matrix of the signal received at the base station (BS). Then, the compressed sensing (CS) technique is utilized to estimate the direction-of-arrival (DOA) of each path. At last, we take advantage of the special structure of the fading channel matrix to eliminate the spurious DOAs and estimate the fading gain of each path at the same time. A special case with only one path from each user to the BS is also discussed, and we exploit the multiple signal classification (MUSIC) algorithm to reduce the complexity. A non-uniform antenna array called the nested array is utilized to increase the array aperture for both the single-path per user and the general cases.

This paper studies adaptive modulation techniques aiming to implement secure transmission in practical communication systems imposed with finite alphabet constraints. As a baseline, the logarithm barrier method is applied to solve the adaptive modulation problem formulated with an inequality constrained secrecy capacity maximization. However, the interested problem requires to jointly solve plural sub-problems to select the best alphabet-set, which incurs a high complexity issue for the baseline technique due to identifying infeasible cases. Hence, we propose a new cache-aided power optimization algorithm that finds the optimal solution with a statistically independent complexity order of the number of the sub-problems. Simulation results obtained in MIMO-ME scenarios verify the effectiveness of the new cache-aided bisection (C-bisect) method that it achieves normalized throughput performance of 0.95.

Signal-to-leakage-and-noise ratio (SLNR)-based transmit precoding techniques are preferable options to perform secure transmission in a low to moderate signal-to-noise ratio (SNR) regime. The conventional SLNR-based techniques assume that a legitimate receiver can estimate and equalize its precoded virtual channels often exhibiting frequency selective property. However, in Internet-of-Things (IoT) systems, lowcost terminals do not always have such complex receivers. We hence propose a new secure transmission scheme for future broadband IoT systems, where the joint SLNR-minimum mean square error (MMSE)-based precoding is performed so that a legitimate terminal assuming a linear complexity receives secret information successfully. Moreover, the proposed scheme adaptively determines transmission rates according to ergodic capacities. Simulation results verify that the proposed method improves the transmission rates significantly while preventing active eavesdroppers from correct receiving.

Full-duplex (FD) communication enables a device to transmit and receive at the same time and on the same frequency. It has the potential to double the capacity of the half-duplex (HD) system. In a multiuser system, however, FD could also double the interference between users which hinders improvement of the capacity. In this paper, we consider resource allocation in a FD multi-cell system to mitigate the interference and exploit the potential gain of FD communication. Due to high complexity of the problem, an ant colony optimization (ACO) based algorithm is proposed to obtain a good performance with reasonable complexity. To the best of our knowledge, the proposed method is the first real multi-cell ACO in the literature applied to a system that allows FD and HD switching. Simulation results show that the proposed algorithm outperforms an existing greedy search method when the number of resource blocks becomes large and the optimization problem becomes complex. By combining the advantages of the ACO algorithm and greedy search, the resultant algorithm yields an even better performance.

This paper considers a grant-free uplink scenario in which the user activity (UA), the timing offsets (TOs), and the channel state information (CSI) of user equipments (UEs) are unknown to the serving base station (BS). In this scenario, the number of potential UEs is large while only a few UEs are active. Due to the sparse nature of the UA, a detection algorithm using approximate message passing (AMP), a compressed sensing (CS) algorithm, is proposed to recover the UA, TOs, and CSI. The proposed algorithm maps the asynchronous system to a virtual system and applies AMP to it. After AMP converges, to minimize the detection error probability, a Bayes test is derived and utilized. Besides, state evolution (SE) analysis is conducted on the virtual system to predict the performance of the proposed algorithm. Simulation results show that when the number of pilot symbols is large enough, the proposed algorithm can achieve the same detection error probability and channel estimation error as those of an ideal system in which the UEs are synchronized. Analytical results show that SE is able to predict the minimum number of pilot symbols needed to achieve a required detection error probability, and predict the performance when the number of pilot symbols is large.

Loop interference (LI) is the main performance-limiting factor in full-duplex (FD) relaying systems. In this paper, we propose using improper Gaussian signaling (IGS) in joint source and relay transmission to achieve a better LI resistance and, as a result, a better end-to-end system throughput in energy harvesting (EH) enabled FD relaying systems. An alternating optimization (AO) algorithm is proposed to solve the challenging design problem of finding the optimal transmission with IGS at both the source and relay, as well as the optimal power-splitting (PS) factor at the EH-enabled relay. The relationship between the PS factor and the optimal pseudo-variances is derived in closed form. Numerical results demonstrate the superior throughput performance yielded by IGS at the same LI level, and suggest the possibility of employing IGS as a replacement of a sophisticated LI canceller in practical FD relaying systems.

Full duplex (FD) communication can potentially provide double spectral efficiency as compared to the conventional half duplex (HD) scheme, thus it is being considered for the next generation wireless networks. To achieve the potential of FD communication in a multi-user network, user pairing and power allocation, which usually require accurate knowledge of the channel state information (CSI), are very important for alleviating the effect of the self-interference (SI) and inter-user interference (IUI). However, the cost (e.g., pilot and signaling overhead) of acquiring accurate CSI is usually high, especially for acquiring the CSI between user equipments (UEs). To trade off between system performance and the cost of acquiring CSI, this work considers that the base station (BS) has only the distance information (equivalent to average CSI) between the BS and the UEs. Based on the distance information, the problem of maximizing the sum rate in a single cell multiuser network subject to maximum power constraints and minimum required signal to interference plus noise power ratio (SINR) is formulated, and a heuristic algorithm to approach the solution is proposed. Simulation results show that the proposed algorithm can effectively exploit the potential gain of FD communication with reasonable system overhead and complexity.

Massive multiple-input multiple-output (MIMO) will be an important ingredient in millimeter-wave (mmWave) cellular communication systems. A natural application of massive MIMO is simultaneous transmission to multiple users. Unfortunately, the hardware constraints in massive MIMO make it difficult to apply the conventional fully digital beamforming techniques, especially in the mmWave bands. Thus hybrid beamforming (HB) in which the overall beamformer consists of a low-dimensional digital beamformer followed by an analog beamformer has been proposed for reducing the number of costly radio frequency (RF) chains in massive MIMO systems. This paper considers an HB design for multi-user massive MIMO systems. We design a sub-optimal analog precoder based on the downlink-uplink duality. To support the general situation where the number of RF chains is not necessarily equal to the number of users, we propose a greedy selection algorithm to allocate RF chains. Finally, we consider the hardware impairment in analog part and extend the proposed algorithm to support the use of finite resolution phase shifters. Simulation results demonstrate that the proposed HB method makes a better tradeoff between complexity and performance compared with existing methods.

For rate optimization in interference limited networks, improper Gaussian signaling has shown its ability to outperform conventional proper Gaussian signaling. In this paper, we study a weighted sum-rate maximization problem with improper Gaussian signaling for the multiple-input multiple-output interference broadcast channel. To solve this nonconvex and NP-hard problem, we propose an effective separate covariance and pseudo-covariance matrices optimization algorithm. In the covariance optimization, a weighted minimum mean square error algorithm is adopted, and in the pseudo-covariance optimization, an alternating optimization (AO) algorithm is proposed, which guarantees convergence to a stationary solution and ensures a sum-rate improvement over proper Gaussian signaling. An alternating direction method of multipliers-based multi-agent distributed algorithm is proposed to solve an AO subproblem with the globally optimal solution in a parallel and scalable fashion. The proposed scheme exhibits favorable convergence, optimality, and complexity properties for future large-scale networks. The simulation results demonstrate the superior sum-rate performance of the proposed algorithm as compared with the existing schemes with proper as well as improper Gaussian signaling under various network configurations.

Turbo channel estimation algorithms can improve estimation accuracy in multiuser (MU) multi-input multi-output (MIMO) systems. However, the conventional least squares (LS) turbo channel estimation technique based on the maximum likelihood approach is difficult to be performed in large MU-MIMO systems since it requires a cubic complexity order O(κ3NT3NR3) for a system constant κ and numbers of NT-transmit and NR-receive antennas. This is because the conventional technique computes inversion of a covariance matrix whose size is proportional to κNTNR. We propose a new low-complexity LS estimation technique that requires a complexity order O(κ3NT3) only by utilizing algebraic property on the covariance matrix. Simulation results shown in this letter verify that the proposed technique significantly reduces processing time without sacrificing the estimation performance.

Inter-block-interference (IBI) caused in the pursuit of spectral efficiency can deteriorate channel estimation performance. For this problem, previously-proposed chained turbo estimation performs IBI cancelation by using the soft replica of the transmitted signal. The IBI cancelation technique can, however, suffer from a mean squared error (MSE) floor problem, since the soft replica is unavailable at the first turbo iteration. The IBI problem can be avoided by using channel impulse response length constraint. Nevertheless, as shown in this paper, the IBI avoidance approach is difficult to perform independently since it requires unbiased second-order statistics. This paper proposes, therefore, a new conditional ℓ1 regularized minimum mean square error channel estimation algorithm by jointly utilizing the IBI avoidance/cancelation and subspace techniques. Simulation results verify that the proposed algorithm solves the MSE floor problem, and, hence, improves the bit error rate convergence performance in realistic IBI channels including the effect of pulse shaping filters.

Multiuser (MU)-multiple-input multiple-output (MIMO) receivers often need to take iterative strategies to cancel multiuser-interference (MUI). Frequency domain turbo equalization is one of the most promising solutions to the MUI problem. It offers a reasonable trade-off between the receiver performance and the computational complexity by assuming cyclic prefix (CP)-transmission. Nevertheless, CP-transmission is not preferable for the battery life of user terminals. Therefore, this paper proposes a new frequency domain multiuser-detection (MUD) technique by extending the chained turbo equalization (CHATUE) to MU-MIMO systems. Simulation results verify that the proposed MU-MIMO CHATUE algorithm is a more reliable option to improve the spectral- and/or energy-efficiency by eliminating the necessity of CP-transmission than by shortening the training sequences or puncturing the coded data bits.

This paper considers noisy Wyner-Ziv coding (WZC), in which a remote noisy source is compressed with side information at the decoder only. The decoder side information is not limited to being Gaussian, thus this noisy WZC problem cannot be transformed into the conventional one tailored for noiseless sources. A new coding structure, named the residual-quantization (RQ) based noisy WZC, is proposed to solve the problem. This scheme explicitly constructs the theoretical auxiliary random variable to facilitate optimal reconstruction of the noisy source. In this two-stage encoder, the noisy source is quantized twice and the quantization error (residue) of the first stage is the input of the second stage. By sending only the quantization index of the second stage to the decoder, the corresponding code rate can theoretically approach the noisy WZC bound. Moreover, the RQ-based noisy WZC is implemented using graph-based codes. The main challenge is that it is necessary to design a codebook that is simultaneously good for source and channel coding for the first stage quantization, since this quantization code also acts as a channel code at the decoder. This problem is solved by constructing a low-density parity check (LDPC) code with edge degrees optimized for channel coding, and enhancing its performance for source coding by using a modified reinforced belief-propagation quantization algorithm. Simulation results show that the noisy Wyner-Ziv bounds can be practically approached by our implementation. In addition, the proposed implementation offers more flexibility in the code rates compared with the existing practical designs, making it more suitable for emerging applications such as fronthaul compression.

With the increasing demand of wireless multimedia services, the multimedia broadcast multicast service (MBMS) is an emerging technology which is adopted in new wireless communication standards to enhance multimedia data transmission. In an MBMS system, all the users subscribing to the service receive multimedia data via the broadcast channel from the base station (BS). To ensure the quality of the broadcast, the MBMS users feedback their channel state information (CSI) to the BS. The BS then selects the best transmission mode according to the users' feedbacks to achieve the optimal result. This CSI feedback operation results in increasing feedback load with the number of users and hence reduces the spectrum efficiency. In this paper, a novel method is proposed to reduce the feedback load of the MBMS systems. The proposed method let the users determine individually whether feeding back their CSI will be critical for the BS to select the transmission mode. If not, a user does not feedback. Different decision rules at the users incur different degrees of MBMS rate loss, which is mathematically analyzed. Through simulations, we show that the proposed method can significantly reduce the CSI feedback load with only a slight impact on the MBMS rate.

This paper considers a general multicast system in which multiple cells cooperate to serve multiple multicast groups in the same radio (i.e., time-frequency) resource. To improve the quality of service (QoS) and reduce the interference among the multicast groups, joint beamforming and power allocation among the cells are employed. By exploiting the concept of downlink-uplink duality and principal angle algorithm, an iterative approach is taken to jointly design the maximum signal-to-interference-plus-noise ratio (SINR) beamforming and power allocation under the per-cell power constraints. Simulation results demonstrate that the proposed method achieves a higher minimum SINR (hence the rate) for the multicast groups compared to the conventional single frequency network (SFN) based scheme and a semidefinite programming (SDP) based scheme in the literature.

Device-to-Device (D2D) communication allows direct communication of a device to another device without traversing a base station. The overlay D2D operation lets D2D users and cellular users use orthogonal radio resources. There is no interference between D2D and cellular links, but the efficiency of frequency reuse is low. The underlay D2D operation, on the other hand, allows D2D and cellular users to occupy the same radio resources. It has better frequency reuse, but the price paid is complicated interference management which usually requires centralized coordination and a significant amount of channel and traffic information exchange. In this paper, a scheme that allows a user to simultaneously transmit cellular and D2D signals is proposed to improve the D2D transmission rate in an overlay system. The proposed scheme has the advantage of frequency reuse, similar to underlay D2D, but does not need centralized interference management. The system design aspects pertaining to the proposed scheme, such as rate maximization, power allocation and scheduling are investigated. System simulations show that the proposed scheme significantly improves the D2D rate with only a slight impact on the cellular rate.

In this paper, we consider a jamming game in wireless networks in which a malicious user tries to jam the transmissions of a user in Gaussian fading multichannel. Both the user and the jammer allocate power to multiple channels with their total power constraints in order to maximize their utilities. We model the utility of the user as a weighted sum of successfully received packets on all channels, and the goal of the jammer is trying to minimize the user's utility. The power allocation strategies at Nash equilibrium of this zero-sum game are derived in closed form and some properties of robustness and worst-case guarantee are presented.

This paper considers a joint beamforming design problem in the multicell multicast system with multiple groups that provide different multicast services. Inspired by previous works in the literature, we apply semidefinite relaxation (SDR) to perform joint beamforming design among the cooperating base stations. Per-cell power constraints are considered which make solving the problem challenging. We propose two algorithms to accommodate the per-cell power constraints while performing joint beamforming. Simulation results show that the proposed algorithms provide better performance compared to the existing multicast methods in the multicell environment.

Dynamically choosing the time-division duplex (TDD) configuration in Long-Term Evolution (LTE) results in intercell interference. Among various interference types, the downlink-to-uplink interference is the strongest due to the much larger downlink (DL) transmission power from a base station than the uplink (UL) transmission power from a user equipment (UE). Although coordinating the neighboring base stations to operate in the same UL/DL configuration is a way to mitigate the interference, the flexibility of TDD is sacrificed. In this paper, we discuss an interference cancellation method exploiting the cloud radio access network (C-RAN) architecture. The downlink- to-uplink interference is cancelled by utilizing the knowledge of the downlink signal available at the cloud server. Simulation results show the effectiveness of this method, which maintains the flexibility of dynamically choosing the UL/DL configuration according to the traffic demand in the TDD system.

This paper considers the multiantenna multiple-access relay channel (MARC), in which multiple users transmit messages to a common destination with the assistance of a relay. In a variety of MARC settings, the dynamic decode-and-forward (DDF) protocol is very useful due to its outstanding rate performance. However, the lack of good structured codebooks so far hinders practical applications of DDF for MARC. In this work, two classes of structured MARC codes are proposed: 1) one-to-one relay-mapper-aided multiuser lattice coding (O-MLC); and 2) modulo-sum relay-mapper-aided multiuser lattice coding (MS-MLC). The former enjoys better rate performance, whereas the latter provides more flexibility to tradeoff between the complexity of the relay mapper and the rate performance. It is shown that, in order to approach the rate performance achievable by an unstructured codebook with maximum-likelihood decoding, it is crucial to use a new K-stage coset decoder for structured O-MLC instead of the one-stage decoder proposed in previous works. However, if O-MLC is decoded with the one-stage decoder only, it can still achieve the optimal DDF diversity-multiplexing gain tradeoff in the high signal-to-noise ratio regime. As for MS-MLC, its rate performance can approach that of the O-MLC by increasing the complexity of the modulo-sum relay-mapper. Finally, for practical implementations of both O-MLC and MS-MLC, practical short-length lattice codes with linear mappers are designed, which facilitate efficient lattice decoding. Simulation results show that the proposed coding schemes outperform existing schemes in terms of outage probabilities in a variety of channel settings, especially when the users-to-relay links are better than the other channel links.

For the multiuser multiple-input multiple-output downlink channel, users feedback their channel state information to help base station schedule users and improve system sum rate. This incurs a large aggregate feedback bandwidth which grows linearly with the number of users. In this paper, we propose a novel scheme to reduce feedback load in a scheduled downlink orthogonal beamforming system by allowing users to opportunistically determine the number of feedback bits to use according to multiple decision thresholds. Through theoretical analysis, we show that, while keeping the aggregate feedback load of the entire system constant regardless of the number of users, the proposed scheme almost achieves the optimal asymptotic sum rate scaling with respect to the number of users (i.e., the multiuser diversity). Specifically, given the number of thresholds, the proposed scheme can achieve a constant portion of the optimal sum rate achievable by the system in which all the users always feedback, and the remaining portion (i.e., the sum rate loss) decreases exponentially to zero as the number of thresholds increases. We further consider feedback design by minimizing the number of thresholds and allocating quantization bits. Simulation shows that the proposed scheme can reduce feedback load and utilize limited feedback bandwidth more effectively than the existing feedback methods.

This paper proposes an adaptive mode and modulation coding switching (AMMCS) scheme for multiple-input multiple-output (MIMO) multicasting system. More specifically, in addition to the adaptively chosen modulation and error coding, two types of MIMO modes are adaptively switched, i.e., between spatial multiplexing (SM) mode, which can achieve higher data rate, and spatial diversity (SD) mode, which can provide higher received signal-to-noise ratio (SNR). Analytical equations for scheduling rate and average spectral efficiency are derived for both SD and SM modes in a 2×2 MIMO system. Simulation results well justify our analytical equations and also demonstrate that our proposed scheme can achieve higher scheduling rate when SNR is low and higher spectral efficiency when SNR is high.

In this paper we consider the secure transmission with multiple-input, single-output, single-antenna eavesdropper (MISOSE) in fast fading channels where the transmitter knows perfect legitimate channel state information but only the statistics of the eavesdropper's channel. For the MISOSE channels, the artificial noise assisted beamforming proposed by Goel and Negi is a promising technique, where the artificial noise is imposed on the null space of the legitimate channel to disrupt the eavesdropper's reception. Here we propose a generalized artificial noise scheme which allows the injection of the artificial noise to the legitimate channel. Although the generalized artificial noise may cause the leakage of artificial noise at the legitimate receiver, the secrecy rate can still be improved since the covariance matrix of it is more flexible than the heuristic one selected by Goel and Negi. To fully characterize the proposed scheme, we investigate the optimization of its secrecy rate. We first derive the conditions under which the beamformers of the message bearing signal and the generalized artificial noise being the same is optimal. Based on this choice, the complicated secrecy rate optimization problem over the covariance matrices of the message-bearing signal and the generalized artificial noise can be reduced to a much simpler power allocation problem. We also develop an efficient algorithm to solve this non-convex power allocation problem. Numerical results show that our generalized artificial noise scheme outperforms Goel and Negi's heuristic selection, especially in the near eavesdropper settings. In particular, with the aid of the proposed scheme, the regime with non-zero secrecy rate is enlarged, which can significantly improve the connectivity of the network.

In this paper, we analytically study a random access network that uses the request-to-send and clear-to-send (RTS/CTS) handshake for reservation of transmission time. In the network, nodes initiate data transmission to a common base station (BS) by sending an RTS packet according to a transmission probability. The RTS packet of a node specifies the length of the node's requested data transmission interval, and will be successfully received by the BS if its signal to interference plus noise ratio (SINR) is higher than the capture ratio. The BS will then reply with a CTS packet to grant this node the requested data transmission interval and inform the other nodes not to interrupt. The transmission probabilities of RTS packets of all nodes will determine the average throughput and power consumption of each node. The set of all possible throughputs that can be achieved by the network is called the throughput region. We characterize the throughput region and provide an upper bound on the total transmission power consumption over the throughput region at the optimal operating point. Specifically, the upper bound corresponds to one of three points in the throughput region depending on the fraction of time occupied by the RTS packets.

Clustered communication has been considered as one key technology for supporting machine-to-machine (M2M) wireless networks with a large number of communicating devices. Unlike related work that focuses on clustering with simple or no wireless interference model at the physical layer, in this paper we investigate the optimization problem of cluster formation and power control for interference-limited M2M communications. We consider a scenario where machines that form in clusters are allowed to reuse the spectrum occupied by human devices through proper transmission power control. To maximize the number of machines that can communicate while meeting the data rate constraints of human devices and machines themselves, we formulate a mixed-integer non-linear programming (MINLP) problem. Since the MINLP problem becomes too complex when the number of machines increases, we propose an algorithm that transforms the problem into a coalition structure generation sub-problem embedded with a linear power control sub-problem. The proposed algorithm is an anytime algorithm and hence the length of the running time can be arbitrarily controlled while yielding a feasible solution with the desired quality. Compared with other approaches for solving the original MINLP problem, we show through numerical results that the proposed algorithm can effectively solve the target problem and allow machines to achieve better spatial reuse with human devices in interference-limited M2M communications.

With the basic features necessary to support Heterogeneous Networks now being incorporated into LTE-Advanced, the next step is to look forward to future evolution of Heterogeneous Networks. While active and extensive discussions are presently progressing in the 3GPP standards community, this paper first provides a review of the current LTE-Advance capability and specification support and an overview of the likely development and trends for the future specifications. Deployments of heterogeneous networks now provides operators an important tool to address growing traffic demand beyond the planned initial network roll-out. This will eventually leads to comparison to and advancement towards coordinated multipoint transmissions and receptions as a possible evolution path from the Release 10 co-channel single point transmission and reception technique. The paper explores the possible enhancements and different evolution paths highlighting their benefits and challenges.

Recently, there has been an increasing interest in the deployment and management of femto base stations (BSs) to optimize the overall system performance in macro-femto heterogeneous networks. While deployment of femto BSs is typically not as planned as that of pico BSs, given a number of femto BSs to be distributed to candidate customer sites, questions regarding the optimal deployment locations and transmission configurations still need to be answered. In this paper, we formulate a joint optimization problem involving deployment location, cell selection, and power control to maximize the number of users that can be supported for a given number of femto BSs to be deployed in the macro cell. Since the formulated problem belongs to mixed-integer non-linear programming (MINLP), we propose an anytime algorithm that can yield a desirable solution within proper time limit. Specifically, based on the concept of coalition structure generation, the algorithm decouples the problem into the cluster formation sub-problem and power control sub-problem to find the optimal cluster head (femto BS location), cluster membership (cell selection), and transmission power in an iterative fashion. Evaluation results presented in this paper show that the proposed algorithm can effectively solve the problem with better complexity-optimality tradeoffs compared to baseline approaches.

Wyner-Ziv coding (WZC) is a compression technique using decoder side information, which is unknown at the encoder, to help the reconstruction. In this paper, we propose and implement a new WZC structure, called residual WZC, for the quadratic-Gaussian Wyner-Ziv problem where side information can be arbitrarily distributed. In our two-stage residual WZC, the source is quantized twice and the input of the second stage is the quantization error (residue) of the first stage. The codebook of the first stage quantizer must be simultaneously good for source and channel coding, since it also acts as a channel code at the decoder. Stemming from the non-ideal quantization at the encoder, a problem of channel decoding beyond capacity is identified and solved when we design the practical decoder. Moreover, by using the modified reinforced belief-propagation quantization algorithm, the low-density parity check code (LDPC), whose edge degree is optimized for channel coding, also performs well as a source code. We then implement the residual WZC by an LDPC and a low-density generator matrix code (LDGM). The simulation results show that our practical construction approaches the Wyner-Ziv bound. Compared with previous works, our construction can offer more design flexibility in terms of distribution of side information and practical code rate selection.

Clustering of machines for better spatial reuse has been considered as one key technology for supporting machine-to-machine (M2M) communications with a large number of communicating devices. Unlike related work that focuses on greedy clustering algorithms without interference control, in this paper we consider a scenario where machines through joint cluster formation and power control are allowed to opportunistically use the spectrum occupied by human devices for interference-limited M2M communications. To maximize the number of machines that can communicate without violating the QoS constraint of the human device, we formulate a mixed-integer non-linear programming (MINLP) problem to determine the optimal cluster structure and power control. We then propose an anytime algorithm based on simulated annealing to solve the MINLP problem under a high density of machines. Compared with the approach of directly solving the MINLP problem and the approach of separately performing cluster formation and power control, we show through numerical results that the proposed algorithm can effectively solve the target problem while striking a better performance tradeoff between complexity and optimality.

In this paper, we consider a channel-aware ALOHA network in which users have the knowledge of their own channel state information (CSI) and exploit this decentralized CSI by utilizing CSI-based transmission schemes. The system throughput is investigated with multi-region transmission schemes under the signal-to-interference-plus-noise ratio (SINR) capture model. We discover that the two-region transmission scheme performs well enough for maximizing the throughput.

In this paper we consider secure transmission for the multiple-input, multiple-output, single-antenna-eavesdropper systems with perfect information of the main channel and only the statistics of the eavesdropper's channel state information known at the transmitter. We adopt the celebrated artificial-noise (AN) assisted beamforming, which was studied by Goel and Negi with the limitation that the AN must be allocated in the null space of the main channel. By removing this limitation, we study the rate optimization problems over the covariance matrices of the signal and the AN. After exploring the structure of the optimal solutions, we show that the original optimization problem can be simplified as a much simpler power allocation problem. Our results show that to improve the rate performance, one may allocate the power of the AN in the directions of the right singular vectors of the main channel. Thus Goel and Negi's AN selection is strictly sub-optimal. Moreover, our simulations show that when the main channel has no null space, the rate performance of our optimized signaling outperforms that of Goel and Negi's significantly.

In this work, we consider an interference-mitigation based cognitive radio system where a secondary transmitter is to communicate with its corresponding receiver without affecting the communication between a primary transmitter-receiver pair. In this case, the secondary transmitter must satisfy a coexistence constraint which requires that no rate degradation occurs at the primary user (PU), even when the latter utilizes only a single-user decoder. To achieve a non-zero rate of the secondary user (SU) under this constraint, Jovicic and Viswanath previously proposed a scheme (referred to as the JV scheme) that utilizes relaying by the secondary transmitter to overcome the interference caused by the simultaneous transmission of the SU's message. In this case, the interference caused by the signals corresponding to PU's message at the secondary receiver (from both the direct and the relay links) is mitigated by employing dirty paper coding (DPC) at the secondary transmitter. However, the interference caused by the SU's message at the primary receiver is not eliminated in this case and, thus, will limit the power (and, hence, the rate) that can be used by the secondary transmitter to transmit its own message. In our work, the use of clean relaying by the secondary transmitter and/or receiver (i.e., relaying without simultaneous transmission of SU's own message) is proposed to improve the quality of the relayed signal and, thereby, increases the rate achievable by the SU. Two improved transmission schemes are proposed: (i) clean relaying by secondary transmitter (CT) and (ii) clean relaying by secondary transmitter and receiver (CTR). The CT scheme utilizes DPC to mitigate interference at the secondary receiver whereas the CTR scheme utilizes coding for multiple access channels with common messages to enable decoding of both PU's and SU's messages at the secondary receiver. The CT scheme can be viewed as a generalization of the JV scheme and, therefore, performs at least as well as the latter. The CTR scheme, on the other hand, is shown to outperform the CT scheme in terms of the multiplexing gain achievable under full channel state information at the transmitter (CSIT) and in terms of the rate achievable with statistical CSIT. Numerical simulations are provided to illustrate these advantages.

This paper considers feedback load reduction for multiuser multiple input multiple output (MIMO) broadcast channel where the users' channel distributions are not homogeneous. A cluster-based feedback scheme is proposed such that the range of possible signal-to-noise ratio (SNR) of the users are divided into several clusters according to the order statistics of the users' SNRs. Each cluster has a corresponding threshold, and the users compare their measured instantaneous SNRs with the thresholds to determine whether and how many bits they should use to feed back their instantaneous SNRs. If a user's instantaneous SNR is lower than a certain threshold, the user does not feed back. Feedback load reduction is thus achieved. For a given number of clusters, the sum rate loss using the cluster-based feedback scheme is investigated. Then the minimum number of clusters given a maximum tolerable sum rate loss is derived. Through simulations, it is shown that, when the number of users is large, full multiuser diversity can be achieved by the proposed feedback scheme, which is more efficient than the conventional schemes.

The cognitive interference channel with unidirectional destination cooperation (CIFC-UDC) is a variant of the cognitive interference channel (CIFC) where the cognitive (secondary) destination not only decodes the information sent from its sending dual but also helps enhance the communication of the primary user. This channel is an extension of the original CIFC to achieve a win-win solution under the coexistence condition. The CIFC-UDC comprises a broadcast channel (BC), a relay channel (RC), as well as a partially cooperative relay broadcast channel (PCRBC), and can be degraded to any one of them. In this paper, we propose a new achievable rate region for the discrete memoryless CIFC-UDC which improves the previous results and includes the largest known rate regions of the BC, the RC, the PCRBC and the CIFC. A new outer bound is presented and proved to be tight for two classes of the CIFC-UDCs, resulting in the characterization of the capacity region.

We consider an ALOHA network in which users have the knowledge of their own channel state information (CSI). In each time slot, each user transmits its packet to the base station (BS) according to a CSI-dependent transmission scheme. A packet is successfully received if its signal to interference plus noise ratio (SINR) is larger than the capture ratio. We analyze the throughput of this network under a threshold-based transmission scheme in which a user transmits only when its channel gain is higher than a threshold. It is shown that in some cases the conventional ALOHA transmission scheme without CSI may outperform the threshold-based transmission scheme in terms of the maximum possible throughput. We give the condition for this phenomenon and find that this phenomenon will not occur if the BS is capable of receiving three or more packets simultaneously. Besides, we present a transmission scheme in which a user only transmits when its channel gain lies in an interval. This scheme includes the threshold-based one as a special case.

We consider secure transmission in fading channels with only the statistics of the eavesdropper's channel state information known at the transmitter. We optimize the celebrated artificial-noise (AN) assisted beamforming, which was studied by Goel and Negi using heuristically selected AN and beamforming directions. We find that Goel and Negi's AN selection is strictly sub-optimal. On the contrary, one may inject AN to the beam direction of the message to improve the secrecy rate performance. We prove that for a multiple-input, single-output, single-antenna-eavesdropper system, the optimal transmission scheme is a beamformer which is aligned to the direction of the legitimate channel. We then prove that, for the part of the AN in the null space of the legitimate channel, uniform power allocation is optimal. We also provide the necessary condition for the proposed AN selection to be optimal. Simulation results show that our AN selection outperforms Goel and Negi's, especially when the legitimate user's channel quality is poor. In particular, when AN assisted beamforming is applied, the region with non-zero secrecy rate is enlarged, which can significantly improve the connectivity of secure networks.

The dynamic decode-and-forward (DDF) protocol for the multiple access relay channel (MARC) with quasi static fading is evaluated using the Zheng-Tse diversity-multiplexing tradeoff (DMT). We assume that there are two users, one half-duplex relay, and a common destination, each equipped with single antenna. For the Rayleigh fading channel, the DDF protocol is well known and has been analyzed in terms of the DMT with the infinite block length assumption by Azarian et al. However, to make the protocol feasible, the practical constraint of finite block length must be enforced, which may result in a loss in the DMT. Another practical effect not considered in the infinite block length DDF protocol is the possible decoding error at the relay. By carefully dealing with these practical issues due to finite block length, we characterize the finite block length DMT of the DDF protocol. We further consider the situation where the destination does not have a priori knowledge of the relay decision time at which the relay switches from listening to transmitting, and show that the optimal DMT is still achievable as if there is no decoding error at the relay. Therefore, the assumption of error-free decoding at the relay and additional protocol overhead to communicate the decision time are not needed for the DDF to achieve the optimal DMT.

In this paper, we study the spectrum access problem in cognitive radio networks with the objective to maximize the expected throughput of cognitive users. We show that the performance of a uniform access policy that uniformly selects one channel to sense, independent of the primary users' behaviors on the channels, is close to that of the optimal randomized access policy when there are a large number of contending cognitive users. We also characterize the throughput taking the energy constraint of cognitive users into account, and present a unified PHY/MAC design to improve the throughput.

Linear-assignment Gel'fand-Pinsker coding (LA-GPC) is a coding technique for channels with interference known only at the transmitter, where the known interference is treated as side-information (SI). As a special case of the LA-GPC, dirty paper coding has been shown to be able to achieve the optimal interference-free rate for SI channels with perfect channel state information at the transmitter (CSIT). In the cases where only the channel distribution information at the transmitter (CDIT) is available, LA-GPC also has good (sometimes optimal) performance in a variety of fast and slow fading SI channels. In this letter, we design filters in the nested lattice based coding to make it achieve the same rate performance as the LA-GPC in multiple-input multiple-output (MIMO) channels. Compared with the random Gaussian codebooks used in previous works, our resultant coding schemes have algebraic structures and can be implemented in practical systems. Simulations in slow-fading channels are provided, and near interference-free error performance is obtained. The proposed coding schemes can serve as the fundamental building blocks to achieve the promised rate performance of MIMO Gaussian broadcast channels with CDIT or perfect CSIT.

An efficient finite rate channel feedback design for multiuser multi-input multi-output (MIMO) downlink beamforming systems with individual signal-to-interference-plus-noise ratio (SINR) constraints is proposed. We find that part of the decomposed channel matrix is irrelevant to the performance, and can be discarded to reduce the feedback load. The remaining information is further decomposed into two parts, and we find that unevenly quantizing these two parts is better than traditionally quantizing the whole matrix evenly. We then show that linearly scaling the number of quantization bits for only one of these two parts is sufficient to maintain a bounded system performance loss. Thus quantization bit allocation between these two parts can be easily done for different signal-to-noise ratios (SNR). Simulation results verify our analysis and show that the proposed design outperforms the existing scheme.

In this paper, we aim to maximize the weighted sum rate of Orthogonal Frequency Division Multiplexing (OFDM) relaying systems. In the considered system we jointly optimize subcarrier pairing in two consecutive time slots and power allocation on each subcarrier in each time slot. In addition, the destination combines the signals from the source and the relay pertaining to the same message in each two time slots. This is motivated by the lack of discussion in the literature on joint optimization with destination combining. It is assumed that the channel state information is known to the source. Decode-and-forward and half-duplex strategies are considered when the relay is used. Both total and individual power constraints for the source and the relay are investigated. Based on the optimization results, algorithms to achieve feasible solutions are also proposed. Simulation results show that the proposed algorithms almost achieve the optimal weighted sum rate, and outperform the existing methods in various channel conditions.

In this paper, we consider the problem of power level selections under an average power constraint in slotted ALOHA networks. In the network, each node chooses a power level from a pre-determined power level set based on a probability for each access attempt. The derivation of the probability for maximizing the throughput is difficult. In addition, nodes may not always obey the given algorithm in a distributed network because a misbehaving node might gain better performance at the expense of the others. To prevent the potential of misbehavior, we derive a cheat-proof algorithm based on game theory, which will make no nodes in the network want to deviate from the algorithm. Further, we show the throughput loss of the cheat-proof algorithm compared to the optimal one, and show the occurrence of unjust situation if the property of cheat-proof is not taken into account.

In a multiuser system, independent time-varying channels among different users can be exploited to provide multiuser diversity (MUD) gain and increase the system throughput. For the downlink channel, this requires the users to feedback their channel state information (CSI) to the base station (BS), which incurs a large aggregate feedback load, especially when the number of users is large. In this paper, we propose a novel scheme to reduce the feedback load in a downlink orthogonal space division multiple access (SDMA) system by allowing the users to dynamically determine the number of feedback bits to use according to multiple thresholds. These thresholds are derived from the statistics of the signal-to-interference-plus-noise ratio (SINR). Through simulation, we demonstrate that the proposed scheme is more efficient than the existing feedback methods, and it achieves the same sum rate growth as the full CSI feedback scheme. Furthermore, a fast bit allocation method is also proposed for the multi-threshold feedback scheme. Simulation results show that this method achieves almost the same sum rate as that achieved by the the optimal bit allocation algorithm.

We derive both the optimal and the game-theoretic (cheat-proof) solutions in closed form, to a problem of distributed access with power control in a pairwise interaction network. In this network, each node has an energy constraint in a fixed time unit for using different power levels in each access attempt competing with a randomly selected node. The one with larger power level wins the access. The optimal control for nodes in the network to maximize the number of wining the access as well as the game-theoretic (cheat-proof) control in which no one will deviate to attain higher number of wining the access are fully characterized in this paper.

In this paper, we present the design of cognitive radio in the Rician channel with partial channel state information at the transmitter (CSIT). We replace the dirty paper coding (DPC) used in the cognitive radio with full CSIT by the linear assignment Gel'fand-Pinsker coding (LA-GPC) which can achieve better error performance when there is only partial CSIT. Based on the achievable rate derived from the LA-GPC, two optimization problems under the fast and slow fading channels are formulated. We derive semi-analytical solutions to find the relaying ratios and precoding coefficients. We also show that the parameters derived by the proposed methods converge to the optimal full CSIT solutions in the asymptotic cases. This result verifies the correctness of the proposed methods asymptotically. Moreover, a new coding scheme is proposed to implement the LA-GPC in practice. Simulation results show that the proposed semi-analytical solutions perform close to the optimal solutions found by brute-force search, and outperform the systems based on naive DPC. Simulation results also show that the proposed practical coding scheme can effectively approach the theoretical rate performance.

We propose an algorithm which iteratively computes the transmit-receive beamforming filters and the power allocation matrix to solve the multiuser multi-input multi-output (MIMO) downlink beamforming problem under signal-to-interference- plus-noise-ratio (SINR) constraints. The transmitter is a multi- antenna base-station broadcasting to users. Each user has multiple antennas at the receiver. The beamforming filter is a group maximum SINR filter which exploits intra-group cooperation, and the power allocated to each data stream is adjusted to enhance performance. Simulation results verify the superiority of the proposed algorithm over previous works.

Wyner-Ziv coding (WZC) is a compression technique which uses decoder side-information to help reconstruction. We present a new coding structure using two-stage successive quantization with two codebooks to solve the Wyner-Ziv problem in the quadratic Gaussian case. The optimal Wyner-Ziv bound is proved to be achievable by random coding analysis. Compared to the existing nested-lattice based design approaches, the two component codes in our construction can be designed independently, which simplifies the code design significantly. Moreover, besides the original noiseless setting where the source is directly observed by the encoder, our coding also suits for the noisy WZC problem where the source is observed via a noisy memoryless channel.

We characterize the Nash equilibrium point of the request probability in a network using the Request-to-send / Clear-to-send (RTS/CTS) handshake mechanism for channel reservation, where each node tries to minimize its average power investment selfishly while meeting its average throughput demand over the shared wireless channel to a common base station. The feasible region of throughput demands is then maximized by the optimal data transmission periods and meanwhile the average power investment at the better Nash equilibrium is reduced. In addition, the performance of the optimum design is compared to that in a network without the RTS/CTS handshake mechanism.

Traditional Orthogonal frequency-division multiplexing channel realization methods need transformations of transmission symbols between time and frequency domains and therefore result in quite a high computational complexity. In this paper, a channel realization method only in the frequency domain is proposed to reduce the complexity of simulation. An example following the IEEE 802.16m standard is also given to illustrate the advantage of the proposed method. The results show that the proposed method indeed well and stably approximates the OFDM channel in the IEEE 802.16m environment.

We study a class of space-time codes constructed by linear dispersion encoding that allow low-complexity linear minimum mean square error (MMSE) decoding for a multiple access system. Considering that the information symbols are drawn from square QAM constellations, we optimize rate-one space time code designs with MMSE decoding to achieve minimum bit error rate (BER) for any channel realization. In addition, the performance is further improved with a simple MMSE successive interference cancellation (MMSE-SIC) method. Simulation results compare the proposed design with existing rate-one designs and show that simple rate-one circulant designs are also good candidates for deployment in multiple access systems.

Cognitive radio (CR) has been proposed as an efficient method to reuse the licensed spectrum. It recognizes the primary (licensed) users' signals and adapts its own to minimize the interference it generates. When perfect channel state information is known at the transmitters, the capacity of CR system can be achieved by utilizing the dirty paper coding (DPC). In this paper, we consider the performance of the CR system under both fast and slow fading channels with only channel statistics known at the transmitters. Due to the limited channel state information, the original DPC fails and is replaced by the so-called linear-assignment Gel'fand-Pinsker coding. By carefully designing the parameters based on this preceding, this system has significant rate gains over naively treating primary users' signals as interference for fast and slow fading scenarios.

In this paper we aim to solve the multiuser multi- input multi-output (MIMO) downlink beamforming problem. The transmitter is a multi-antenna base-station broadcasting to users. Each user has multiple antennas at the receiver. A solution of the joint transmit-receive beamforming and power allocation under signal-to-interference-plus-noise-ratio (SINR) constraints in this system is proposed. The beamforming filter is a group maximum SINR filter which exploits intra-group cooperation. Taking advantage of the uplink-downlink duality property, the proposed algorithm iteratively computes the transmit-receive beamforming filters and the power allocation matrix. Simulation results verify the superiority of the proposed algorithm over previous works using per stream maximum SINR method.

We explicitly construct space-time codes for a multiple access system composed of K users transmitting simultaneously to the base station in block-fading channels. Each user encodes its own data independently without cooperation between users. Our codes design uses the idea of linear dispersion encoding together with circulant matrices assigned to each user that allow low-complexity linear minimum mean square error (MMSE) decoding when the channel realization is known to the base station. Moreover, the ergodic sum rate of the proposed design is studied and compared with the sum capacity.

A result of Zheng and Tse states that over a quasi-static channel, there exists a fundamental tradeoff, known as the diversity-multiplexing gain (D-MG) tradeoff. The quest for space-time codes that achieve D-MG tradeoff has generated numerous works. However, these space-time codes generally result in a pretty high peak to average power ratio (PAR) value on each antenna. In this paper, we propose two general ways to reduce PAR without affecting code structures and without any side information being transmitted. Therefore, the modified space-time codes still achieve the D-MG tradeoff. The two methods are both based on constellation shaping. The first method is similar to the method proposed by Kwok except we employ the Hermite Normal Form (HNF) decomposition instead of the Smith Normal Form (SNF); the second one takes the idea of integer reversible mapping. Both techniques lead to an asymptotical PAR value equal to 3 as the constellation size becomes large. Sphere decoding is performed to verify that the proposed PAR reduction methods do not affect the performance of space-time codes.

Recently, the vector dirty paper coding (DPC) achievable rate region has been shown to be the capacity region of a multiple-input multiple-output Gaussian broadcast channel (MIMO GBC). With DPC, the multiuser interference noncausally known at the transmitter can be completely removed. In this paper, we present a vector DPC structure for MIMO GBC. It is a generalization of the single antenna superposition dirty paper coding for the scalar Gaussian dirty paper problem proposed by Bennatan et al. In a theoretical random code setting, this construction is shown to be able to achieve the promised rate performance of the MIMO GBC. We also implement it with existing vector quantizer and capacity-achieving channel coding. Combined with iterative decoding, a design example validates the effectiveness of our methods.

This correspondence presents new rate-1 space-time block codes (STBCs) attending full diversity over every quadrature amplitude modulation (QAM) constellation when the number of Tx antennas is a power of two. From the simulation results, our design performs very closely to the quasi-orthogonal code with constellation rotation over 4-QAM and 16-QAM in the case of four Tx antennas over quasi-static Rayleigh fading channels. Moreover, the proposed codes would not cause any constellation expansion over QAM symbols in contrast with the quasi-orthogonal codes with constellation rotations

In this paper, we improve the peak to average power ratio (PAPR) reduction scheme for multicarrier systems proposed by Collings and Clarkson by applying dirty paper coding with peak power constraint. We compare the bit error rate (BER) performance among conventional orthogonal frequency division multiplexing (OFDM), Collings and Clarkson’s method, and our proposed scheme with bit loading. From simulation we find that when channel coding is considered, Collings and Clarkson’s method is the worst independent of the number of bits loaded. The proposed method performs the best when the number of bits is large and hence is suitable for high speed transmission.

This article presents a set of quasi-orthogonal spacetime block codes for four transmit antennas that achieves full diversity and high coding gain whenever a square lattice constellation is adopted. From the simulation results, the new designs perform very closely to quasi-orthogonal codes with constellation rotations. Without a search of the optimal rotation angle and any constellation expansion, our new codes yield an advantageous transmission scheme for QPSK and 16-QAM modulations.

An expanded effort is underway to support the evolution of the UMTS standard to meet the rapidly developing needs associated with wireless Internet applications. The support of high speed downlink packet access (HSDPA) is provided by means of a new, shared channel called high speed downlink shared channel (HS-DSCH) which is enabled by a number of performance enhancing technologies such as adaptive modulation and coding (AMC), hybrid ARQ (HARQ), fat-pipe scheduling, fast cell selection (FCS) and multiple input multiple output (MIMO) antenna techniques. In this paper, the advantage of FCS is investigated. To avoid the difficulty in HARQ transmission-state synchronization, FCS is allowed only among the cells (sectors) belonging to the same base station. Two FCS approaches are compared in this paper. The user controlled cell selection (UCCS) selects the serving cell based only on the channel quality seen by the user. While a new-network controlled cell selection (NCCS) approach jointly considers channel quality and network loading. It is shown that FCS significantly improves the HSDPA performance at low mobility. Among the FCS schemes, NCCS is superior to UCCS when the load among the cells in the active set is unbalanced.

An expanded effort is underway to support the evolution of the UMTS and cdma2000-1x standards to meet the rapidly developing needs associated with wireless Internet applications. A number of performance enhancing technologies are proposed to ensure high peak and average packet data rates while supporting circuit-switched voice and packet data on the same spectrum. These techniques include adaptive modulation and coding (AMC), hybrid ARQ (H-ARQ) and fat-pipe scheduling. In order to enable these techniques downlink channel quality feedback (CQF) through explicit uplink signaling is necessary. Frequent CQF results in good estimates of downlink channel quality at the base station, which, in turn, improves downlink system performance. However, this comes at the expense of larger uplink signaling overhead, thereby impacting the overall uplink capacity. Infrequent CQF, on the other hand, reduces this signaling overhead in the uplink at the expense of larger errors in the channel quality estimates available at the base station, thereby leading to system performance degradation. In this paper, we present a variable rate CQF scheme that significantly reduces uplink signaling overhead without affecting downlink system performance. In addition to simulation results demonstrating the performance of the proposed scheme, we also compare the reduction in uplink signaling overhead of the said scheme with other known methods.

The radio link control (RLC) for Universal Mobile Telecommunication System (UMTS) is an acknowledgement based transmission protocol. Protocol stalling and deadlock might happen under certain circumstances and thus reduce the system efficiency. In this paper, we propose and investigate three alternative mechanisms with spontaneous retransmissions to prevent protocol stalling. We compare the results indicate that all three methods can prevent protocol stalling quite effectively. In addition, the combined retransmission of the last or the earliest transmitted packet has the best throughput and delay performance and outperforms the other two methods.

UMTS radio link control (RLC) contains a suite of features and options that make it a challenging task for performance evaluation. We develop a periodic-polling-based retransmission model to analyze the RLC protocol. We derive the evolution of the queue length distribution that can be used to construct a Markov chain. While the task of obtaining a closed-form solution for this Markov chain given a general set of system parameters seems to be formidable, we have been able to obtain a closed-form solution for the average system occupancy for some interesting special cases. To validate the efficacy of the analytical model, we perform numerical calculation on the upper and lower bounds of the average packet delay and compare it with the simulation results. The results show that the lower bound derived is very tight.

The radio link control (RLC) protocol in Universal Mobile Telecommunication System (UMTS) contains a suite of features and options which make the protocol very flexible and adaptive to operation in different radio environments and for various applications. We analyze the various features and functions associated with the RLC protocol and evaluate the performance over UMTS specific physical link through simulations. Specifically, we examine the detail behavior of the protocol under various conditions and options, including polling, status transmission mechanism, and packet discard functions. We compare different polling mechanisms and examine their impacts on the delay and throughput as well as acknowledgement overhead. We also compare different discard parameters and service rates and evaluate their impacts on the overall performance. Finally we provide quantitative results for web-browsing traffic which is considered as one of the future applications in 3G wireless networks.

In anticipation of the high demand for wireless data services, several wireless standards are evolving to support packed data more efficiently. In UMTS, a new, shared channel called the high speed downlink shared channel (HS-DSCH) that multiplexes packet data users has been defined. Several performance-enhancing technologies are included in high speed downlink packet access (HSDPA): adaptive modulation and coding (AMC), hybrid ARQ (HARQ), scheduling etc. HARQ algorithm plays a critical role in HSDPA performance. HARQ techniques are classified in terms of the combining method (chase or incremental redundancy, IR), protocol timing (synchronous or asynchronous) and adaptivity (if modulation/code-rate can be changed for retransmission or not). In previous work (Das et al. 2001), an adaptive, asynchronous, incremental redundancy (A/sup 2/IR) scheme was proposed and shown to provide substantial gains over other HARQ options. In this paper, the design and performance aspects of A/sup 2/IR in the code domain (as against the time domain in Das et al.) are considered. Due to the higher bandwidth of the UMTS channels compared to cdma2000 or HDR, it is expected that code-division multiplexing (CDM) of users will be needed to "fill the data pipe" instead of pure time-division multiplexing. The paper also analyzes tradeoffs that are unique to implementing A/sup 2/IR with CDM. A/sup 2/IR with a fixed TTI is now part of UMTS Release 5.

An expanded effort is underway to support the evolution of the UMTS standard to meet the rapidly developing needs associated with wireless Internet applications. The support of high-speed downlink packet access (HSDPA) is provided by means of a new, shared channel called high speed downlink shared channel (HS-DSCH) which is enabled by a number of performance enhancing technologies such as adaptive modulation and coding (AMC), hybrid ARQ (HARQ), fat-pipe scheduling, fast cell site selection (FCSS) and multiple input multiple output (MIMO) antenna techniques. To fully benefit from these technologies, one must guarantee fast and reliable control message exchange between the base station and the user terminals. The downlink signaling is done through the use of shared control channels (SCCH) accompanied with each HS-DSCH. Since the SCCHs, HS-DSCH, and voice channels share the same resources (power, bandwidth), control signalling is often improved at the cost of system resources and capacity. In this paper, we evaluate the performance of the SCCH. The challenges and tradeoffs in the SCCH design will also be discussed.

Joint channel estimation and decoding in a time-varying Rayleigh fading channel is considered. Knowing that the optimal solution or even the truncated near-optimal solution using iterative processing has an exponential complexity which hinders the practicability, a reduced complexity approach is proposed. This approach keeps the existing channel estimation and decoding schemes almost intact, while applying iterative processing to effectively exchange information between them. Thus, the complexity is rendered linear, and estimator adaptability can be easily established. We apply this approach to pilot symbol-assisted modulation (PSAM) and differentially modulated systems. It turns out that the performance is improved and the robustness to fading parameters is enhanced. Through simulations, we also show that the proposed method performs almost as well as the near-optimal design.

We consider the design of an array processor for space-time coded multi-antenna systems. As an alternative to the previously proposed zero-forcing method, in this paper, the maximum signal-to-noise ratio (SNR) criterion is used to obtain a balance between interference suppression and noise enhancement. Although the same in concept, this work differs from the conventional minimum mean-squared error method in that there is more than one desired signal dimension each corresponding to one of the space-time coded streams. It is shown that the number of linear filters required by the maximum SNR array processor is no more than the dimension of the signal space or the number of collaborating transmit antennas. The advantages of this design are highly improved performance and reduced decoding complexity.

Power control is important in maintaining the communication link quality under fading and interference situations. In recent years, research on power control has been conducted toward reducing power consumption while maintaining reliable link quality. These previous works, however, did not try to optimize power control algorithms under practical constraints. In this paper, we first observe and provide some insights into the previous works on different aspects of power control schemes. These observations motivate us to propose a new power control scheme which has several novel features: it uses an adaptive optimal quantizer at the receiver for transmitting discrete feedback information and an adaptive quantization scaler/restorer followed by a loop filter at the transmitter. Optimal quantization minimizes the feedback information loss and the additional power control error caused by it, while the loop filter can be designed to achieve the lowest power control error. Optimization of the loop filter requires some computational power. Fortunately, filter self-design capability can be implemented. In that case, closed-loop power control can be seen as an instance of a general channel identification problem. Intuitive explanation, together with analysis and simulation results of the proposed scheme will be given.

An expanded effort is underway to support the evolution of the UMTS standard to meet the rapidly developing needs associated with wireless Internet applications. The support of packet-switched high-speed data users is provided by means of a new, shared channel called HS-DSCH (high speed downlink shared channel) that preferably serves one packet data user at a time in a time-multiplexed manner. A number of performance enhancing technologies are included in the high speed downlink packet access (HSDPA) proposal to ensure high peak and average packet data rates while supporting circuit switched voice and packet data on the same spectrum. These techniques include adaptive modulation and coding (AMC), hybrid ARQ (HARQ), fat-pipe scheduling, fast cell site selection (FCSS) and multiple input multiple output (MIMO) antenna techniques. In this paper, we provide the performance comparison of different HARQ schemes being considered for HSDPA.

In attempting to find a spectrally and power efficient channel code which is able to exploit maximum diversity from a wireless channel whenever available, we investigate the possibility of constructing a full antenna diversity space-time turbo code. As a result, both three-antenna and two-antenna (punctured) constructions are shown to be possible and very easy to find. To check the decodability and performance of the proposed codes, we derive non-binary soft-decoding algorithms. The performance of these codes are then simulated and compared with two existing space-time convolutional codes (one has minimum worst-case symbol-error probability; the other has maximal minimum free distance) having similar decoding complexity. As the simulation results show, the proposed space-time turbo codes give similar or slightly better performance than the convolutional codes under extremely slow fading. When fading is fast, the better distance spectra of the turbo codes help seize the temporal diversity. Thus, the performance advantage of the turbo codes becomes evident. In particular, 10/sup -5/ bit-error rate and 10/sup -3/ frame-error rate can be achieved at less than 6-dB E/sub b//N/sub 0/ with 1 b/s/Hz and binary phase-shift keying modulation. The practical issue of obtaining the critical channel state information (CSI) is also considered by applying an iteratively filtered pilot symbol-assisted modulation technique. The penalty when the CSI is not given a priori is about 2-3 dB.

Use of multiple antennas at the transmitter and the receiver to increase the information capacity has received considerable attention. To exploit the capability of such systems in a practical way, it is of interest to ask if there are good codes with reasonable decoding complexity. Another question of interest is the simplicity of design. This issue is particularly important in the case where the number of antennas in transmitter and receiver are large and a space-time code may be to complex to design and decode. We illustrate a class of codes which are simpler to design and the interference across antennas is suppressed by linear processing at the receiver. The performance of such codes is excellent and much better than the group interference suppression techniques employed in conjunction with the space-time codes. Use of error detection schemes is shown to further improve the performance without much change in the design of codes and decoding complexity.

A new scheme termed orthogonal code division multiplexing (OCDM) is proposed for digital subscriber line (DSL) applications. Through the use of serial to parallel conversion and orthogonal codes, a "spreading gain" is achieved against narrowband interference without expanding the required transmission bandwidth of the information signal. Groups of orthogonal codes with different spreading gains and bandlimited (chip) filtering are used together with M-PAM data modulation. Spectral matching (to input power density that achieves the capacity of the copper cable channel) is performed followed by throughput optimization under a symbol error rate (SER) constraint in order to select the system parameters. The OCDM/DSL system performance is evaluated for several scenarios of interest.

We consider the design of array processor for space-time coded multi-antenna systems. While the zero-forcing method was employed by Tarokh, Naguib, Seshadri and Calderbank (see IEEE Transactions on Information Theory, vol.45, no.4, p.1121-28, 1999), in this paper we seek to obtain a balance between interference suppression and noise enhancement. Although same in concept, this work differs from the conventional minimum mean square error (MMSE) method in that there are more than one desired signal dimensions each corresponding to one of the space-time coded streams. In this case, minimizing the mean squared error (MSE) involves averaging over data modulation and may complicate the presentation. Instead, maximizing the signal-to-noise ratio (SNR) can be handled more concisely. It will be shown that the number of linear filters required by the maximum SNR array processor is no more than the dimension of the signal space or the number of collaborating transmit antennas. The advantages of this design are highly improved performance and reduced decoding complexity.

Joint channel estimation and decoding in a time-varying Rayleigh fading channel is considered. Knowing that the optimal design has an exponential complexity which hinders the practicability, a reduced complexity approach is proposed. This approach keeps the existing channel estimation and decoding schemes almost intact, while applying the turbo or iterative processing principle to enable information exchange between them. Thus the complexity is rendered linear; and the filter adaptability can be easily established. We apply this approach to two commonly used modulation schemes for noncoherent detection, namely, pilot symbol assisted modulation (PSAM) and differential modulation, with the intention to overcome certain disadvantages seen in their demodulation. It turns out that the performance is improved and the robustness is enhanced. In this paper, we first give the system descriptions of the two applications. Their performances are then simulated and compared with the existing systems. To reveal the tradeoffs in practical applications, the two new designs are also compared with each other in terms of throughput, complexity, performance, and robustness.

We consider the application of multicarrier modulation in a wireless cellular network in order to enable high-data rate communication and alleviate the multipath induced intersymbol interference (ISI). In this scenario, power control becomes crucial in enhancing the spectral and power efficiency. A conventional approach of maintaining the same link quality for all the subchannels, in other words, disregarding any possible post-demodulation processing, is considered first. This approach appears to have increasing power consumption as the number of subchannels increases. It also deteriorates the power control stability and convergence properties in a multicell network. We attribute this phenomenon to lack of frequency diversity exploitation, and thus, we propose to use channel coding and soft decoding as vehicles to profit from the (frequency) diversity advantage in addition to the coding advantage. Based on the soft decoding performance bound, a power allocation and control algorithm is proposed. It is shown through simulations that the proposed algorithm improves the power efficiency as the number of subchannels increases. It also provides a better convergence property and is able to "detect" and eliminate ill-conditioned subchannels. The advantages of using multicarrier modulation are thus reassured. Besides these enhancements, the proposed algorithm is simple and feasible in that it consists of only the traditional closed-loop power control algorithm and a target signal-to-interference ratio (SIR) reassignment at the receiver. Detailed channel information feedback from receiver to transmitter is not required.

The use of orthogonal CDMA for uplink satellite communication requires that all user codes arrive at the satellite despreader at a common time. To this end schemes for network synchronization among all users are necessary; these involve two stages: code acquisition and code tracking. We propose a code tracking loop that extends between the satellite and the ground terminal. The traditional code tracking loop is broken into two segments: the satellite segment of the loop conducts the phase difference extraction; while the ground segment of the loop at the Earth station performs the filtering and phase adjustment. The major difference of this tracking system and the traditional loops is the long propagation delay entering the loop delay and secondarily the satellite motion. The optimization of the tracking loop filter is undertaken with respect to the steady state error and the variance of the timing error. The performance of the code tracking loop scheme is evaluated for a single-beam fully-loaded SATCOM system.

Power control is important in maintaining the communication link quality under fading and interference situations. In previous years, research on power control has been conducted towards reducing the power consumption while maintaining reliable link quality. These previous works, however, did not try to optimize the power control algorithms under practical constraints. In this paper, we first provide a critical review of the previous works on different aspects of power control schemes. We then propose a new power control scheme which has several novel features: it uses an adaptive optimal quantizer at the receiver for transmitting discrete feedback information and an adaptive quantization scaler/restorer followed by a loop filter at the transmitter. Intuitive explanation of the effectiveness of the proposed design is provided. Analysis and simulation results are also given.